Decision Science in Action

The objective of this article is to propose a design of a personalized recommendations application for restaurants owners which can be used by the customers of the given credit/debit card issuer. The developed recommendation application can be installed as mobile application in the mobile phone of the customers. The recommendation engine will use machine learning algorithms and predictive analytics techniques to derive information from  the credit transaction data, mobile location data, social media data (Facebook, Twitter), public data (Yelp.com/Bundle.com etc.), mobile browser data and data of the restaurants*. The recommendation engine will have two modules. First module will use the clustering algorithm to derive actionable information from credit card data and restaurants data. It will also use the data mining techniques to integrate the useful information available in the web space with restaurant data (explained later). This module will execute in server of the bank...

/* if the data set exists, then conditionally execute the step(s). %sysfunc checks the availability of the data in the library location. It means it checks historical sas data. It generates the system error if the not is data available at the defined library  */ %let dsname=&dataval.MKT_DATA;  /**** declaring data set name with library*****/ %macro warning1(name); %if %sysfunc(exist(&name)) %then %do; Proc printto log="&logfile.\WarningLog..txt" new;     /*** printing log in the text file at specifile location &logfile****/ run; %Put WARNING :- &name does not exists; Proc printto  ; Run; %end; %else %do; Proc printto log="&logfile.\WarningLog.txt" ; run; %put &name exists; Proc printto  ; Run; %end; %mend ; %warning1(&dsname); /**** Pros:  If any sas process is dependent on the existence of the data then we can use this macro***/ /**** Cons:  *Even if the SAS data set is a...